摘要：Predicting future climatic conditions at high spatial resolution is essential for many applications and impact studies in science. Here, we present monthly time series data on precipitation, minimum- and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation at ~5鈥塳m spatial resolution globally for the years 2006鈥?100. We validated the performance of the downscaling algorithm by comparing model output with the observed climate of the historical period 1950鈥?969.
